Concept learning by fuzzy k-NN classification and relevance feedback for efficient image retrieval

Authors:
Hossein Nezamabadi-pour;Ehsanollah Kabir
Affiliations:
Department of Electrical Engineering, Tarbiat Modarres University, P.O. Box 14115-143, Tehran, Iran and Department of Electrical Engineering, Shahid Bahonar University of Kerman, P.O. Box 76169-13 ...;Department of Electrical Engineering, Tarbiat Modarres University, P.O. Box 14115-143, Tehran, Iran
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

A new method for combining visual and semantic features in image retrieval is presented. A fuzzy k-NN classifier assigns initial semantic labels to database images. These labels are gradually modified by relevance feedbacks from the users. Experimental results on a database of 1000 images from 10 semantic groups are reported.